code: def test_frontend_forward_ilens(whisper_frontend):
      input_tensor = torch.randn(
          4, 3200, device=next(whisper_frontend.parameters()).device
      )
      input_lens = torch.tensor(
          [500, 1000, 1600, 3200],
          device=next(whisper_frontend.parameters()).device,
      )
      feats, feats_lens = whisper_frontend(input_tensor, input_lens)
  
      assert feats.size() == torch.Size([4, 10, 384])
      assert torch.equal(feats_lens.cpu(), torch.tensor([2, 3, 5, 10]))
  
file_path: espnet/test/espnet2/asr/frontend/test_whisper.py
imports: import sys
  import pytest
  import torch
  from packaging.version import parse
  from espnet2.asr.frontend.whisper import WhisperFrontend
label_desc: Use image node_id 5 for calling a global function with example usage: test_frontend_forward_ilens(whisper_frontend) without return types